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Quest Training

Data Strategy & Building a Data-Driven Organization Training Course

Helps leaders assess data maturity, align a data strategy with business goals and build the culture and capabilities of a truly data-driven organization.

DOPS · Data & AI Operating ModelsAll Levels#2558ClassroomEnglish , Arabic
Duration
5 Days
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Free substitution at any time · 30+ days' notice: full refund minus 10%. Cancellation policy

Sectors:Data, Analytics & Digital TransformationCategories:Data & AI Operating Models

Course Overview

This advanced practical course develops the strategic capabilities required to build a data-driven organization where data is treated as a business asset and systematically used to improve decisions, performance, risk management, and innovation. The programme connects data strategy with organizational priorities rather than treating data management as a purely technical function. Participants will examine how to assess current data capabilities, define a target data vision, establish strategic priorities, and align data initiatives with business objectives. The course addresses data governance, ownership, quality, architecture, analytics, technology, organizational capabilities, and decision-making. The programme also focuses on the organizational changes required to embed data into everyday management and operational practices. Participants will explore data leadership, accountability, data literacy, performance measurement, adoption, and the barriers that prevent organizations from realizing value from their data. Through practical scenarios, participants will develop data strategy components, prioritize initiatives, define governance structures, assess organizational readiness, and build implementation roadmaps that support sustainable transformation.

Learning Objectives

  • Analyse the strategic role of data in organizational performance and competitive advantage.
  • Assess current data capabilities, maturity, and organizational readiness.
  • Align data strategy with business objectives and strategic priorities.
  • Define a clear data vision, strategic principles, and target operating model.
  • Identify critical data assets, business requirements, and priority use cases.
  • Establish appropriate data governance, ownership, accountability, and decision rights.
  • Develop approaches for improving data quality, accessibility, security, and usability.
  • Evaluate data architecture, technology, analytics, and infrastructure requirements.
  • Strengthen data literacy and data-driven decision-making across organizational functions.
  • Define metrics for measuring the value and effectiveness of data initiatives.
  • Prioritize data transformation initiatives based on business value, risk, and feasibility.
  • Develop a practical roadmap for building and sustaining a data-driven organization.

Who Should Attend

This course is designed for Chief Data Officers, Data and Analytics Managers, CIOs, IT Managers, Digital Transformation Leaders, Business Intelligence Managers, Data Governance Professionals, and senior professionals responsible for organizational data capabilities. It is also suitable for executives, department heads, strategy leaders, risk and compliance professionals, and business managers who need to understand how data can be embedded into strategic and operational decision-making. The programme is particularly relevant to organizations developing enterprise data strategies, digital transformation programmes, analytics capabilities, data governance frameworks, or organization-wide data-driven operating models.

Learning Outcomes

  • Evaluate an organization's current data maturity and strategic readiness.
  • Define a data vision aligned with organizational strategy.
  • Identify priority data assets, business needs, and high-value use cases.
  • Develop strategic data priorities and measurable objectives.
  • Design appropriate governance, ownership, and accountability structures.
  • Identify data quality, accessibility, security, and integration requirements.
  • Evaluate the organizational and technological capabilities needed to support the data strategy.
  • Strengthen data literacy and adoption across business functions.
  • Establish performance measures for data initiatives and business value.
  • Prioritize data programmes using value, risk, complexity, and feasibility criteria.
  • Identify organizational barriers to data-driven decision-making and develop responses.
  • Develop an actionable roadmap for implementing and sustaining a data-driven organization.

Course Outline

Day 1

Data Strategy Foundations & Organizational Data Maturity

  • Strategic value of data as an organizational asset.
  • Characteristics of data-driven organizations.
  • Relationship between business strategy and data strategy.
  • Assessing current data capabilities and maturity.
  • Data maturity across governance, technology, people, processes, and analytics.
  • Identifying organizational data challenges and value gaps.
  • Defining data vision and strategic principles.
  • Identifying critical business questions that require better data.
  • Establishing strategic data priorities.
  • Practical Application: Conduct a data maturity assessment and develop an initial data vision for a selected organization.
Day 2

Data Governance, Ownership & Data Management

  • Principles of enterprise data governance.
  • Governance operating models and decision structures.
  • Data ownership and accountability.
  • Roles and responsibilities for critical data assets.
  • Data quality management and improvement.
  • Data standards, policies, and data definitions.
  • Data security, privacy, and access requirements.
  • Data lifecycle management.
  • Metadata, lineage, and data transparency.
  • Practical Application: Design a governance framework defining ownership, accountability, decision rights, and priority data management requirements.
Day 3

Data Architecture, Analytics & Business Value

  • Strategic role of enterprise data architecture.
  • Data platforms, integration, and accessibility.
  • Data Lakes, Lakehouses, warehouses, and analytical environments.
  • Connecting operational data with analytical capabilities.
  • Business intelligence and advanced analytics.
  • Identifying high-value data use cases.
  • Linking analytics initiatives to measurable business outcomes.
  • Evaluating technology and capability requirements.
  • Balancing innovation, scalability, security, and cost.
  • Practical Application: Develop a target data capability model and identify priority analytics use cases linked to business value.
Day 4

Data-Driven Culture, Leadership & Decision-Making

  • Building a data-driven organizational culture.
  • Executive sponsorship and data leadership.
  • Embedding data into management and operational decisions.
  • Data literacy and capability development.
  • Establishing accountability for data-based decisions.
  • Overcoming resistance and organizational adoption barriers.
  • Using data to improve performance management.
  • Defining data and analytics performance indicators.
  • Communicating data insights to executives and decision-makers.
  • Practical Application: Develop an organizational adoption plan to strengthen data literacy, accountability, and evidence-based decision-making.
Day 5

Data Strategy Implementation, Prioritization & Transformation Roadmap

  • Translating data strategy into executable initiatives.
  • Prioritizing data programmes based on value, risk, and feasibility.
  • Defining strategic data initiatives and measurable outcomes.
  • Developing implementation phases and dependencies.
  • Establishing data strategy governance and progress monitoring.
  • Managing organizational and technology transformation risks.
  • Measuring data programme performance and business impact.
  • Maintaining strategic alignment as organizational needs evolve.
  • Establishing continuous improvement mechanisms for data capabilities.
  • Final Workshop: Develop and present an integrated data strategy and transformation roadmap covering the data vision, maturity priorities, governance model, target capabilities, high-value use cases, organizational enablement, performance measures, and implementation priorities.

Upcoming Dates

Selected date

Beirut · 10 – 14 Oct 2027 · Classroom

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CityDatesPrice per ParticipantEarly Bird
Kuala LumpurScheduled
2 – 6 Nov 2026€4,400—
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LisbonScheduled
9 – 13 Nov 2026€5,400—
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LondonScheduled
16 – 20 Nov 2026€5,600—
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Cape TownScheduled
16 – 20 Nov 2026€5,100—
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MadinahScheduled
23 – 27 Nov 2026€4,200€3,780until 2 Nov
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MadridScheduled
30 Nov – 4 Dec 2026€5,400€4,860until 9 Nov
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MakkahScheduled
30 Nov – 4 Dec 2026€4,200€3,780until 9 Nov
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DubaiScheduled
6 – 10 Dec 2026€4,400€3,960until 16 Nov
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ManamaScheduled
7 – 11 Dec 2026€4,700€4,230until 16 Nov
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MarbellaScheduled
14 – 18 Dec 2026€5,400€4,860until 23 Nov
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MarrakeshScheduled
21 – 25 Dec 2026€4,300€3,870until 30 Nov
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ErbilScheduled
27 – 31 Dec 2026€3,100€2,790until 7 Dec
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MilanScheduled
28 Dec 2026 – 1 Jan 2027€6,000€5,400until 7 Dec
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MunichScheduled
4 – 8 Jan 2027€5,400€4,860until 14 Dec
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MuscatScheduled
11 – 15 Jan 2027€5,300€4,770until 21 Dec
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OnlineScheduled
17 – 21 Jan 2027€1,700€1,530until 28 Dec
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ParisScheduled
18 – 22 Jan 2027€5,700€5,130until 28 Dec
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IstanbulScheduled
18 – 22 Jan 2027€4,700€4,230until 28 Dec
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RiyadhScheduled
25 – 29 Jan 2027€4,200€3,780until 4 Jan
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RomeScheduled
1 – 5 Feb 2027€5,800€5,220until 11 Jan
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JeddahScheduled
7 – 11 Feb 2027€4,200€3,780until 18 Jan
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SalalahScheduled
8 – 12 Feb 2027€5,300€4,770until 18 Jan
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ViennaScheduled
15 – 19 Feb 2027€5,700€5,130until 25 Jan
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AmmanScheduled
21 – 25 Feb 2027€3,100€2,790until 1 Feb
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KigaliScheduled
22 – 26 Feb 2027€5,100€4,590until 1 Feb
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AmsterdamScheduled
1 – 5 Mar 2027€5,400€4,860until 8 Feb
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BarcelonaScheduled
1 – 5 Mar 2027€5,400€4,860until 8 Feb
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BerlinScheduled
8 – 12 Mar 2027€5,800€5,220until 15 Feb
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CairoScheduled
15 – 19 Mar 2027€3,300€2,970until 22 Feb
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AbujaScheduled
15 – 19 Mar 2027€5,100€4,590until 22 Feb
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BeirutScheduled
10 – 14 Oct 2027€4,000€3,600until 20 Sept
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